International Journal of Geographical Information Systems · 1990 · 150 citations · 7 references
EngineeringLand UseSocial SciencesSuch Expressive InadequacyGeographic Information SystemsData ScienceClassical Set TheorySpatial Data ManagementSystems EngineeringData IntegrationData ManagementLand SuitabilityFuzzy Pattern RecognitionCartographyFuzzy LogicSpatial DatabasesFuzzy ComputingGeographic Information RepresentationGeographyFuzzy Information RepresentationSpatial Information SystemDatabase DesignGeospatial SemanticsFuzzy MathematicsConventional Gis SoftwareGeospatial DataData Modeling
Current GIS methods are inadequate because they cannot tolerate imprecision, largely due to the classical set theory membership concept. The paper seeks to improve GIS information processing by developing an alternative membership concept, exploring classical set theory inadequacies, and creating a GIS database for agricultural land resource management with a new land suitability assessment technique. We define a fuzzy relational data model, build a GIS database for agricultural land resource management using this model, develop a new land suitability assessment technique, and test the methods with North Java data in Arc Info. The fuzzy representation reduces information loss and improves data analysis, as demonstrated by tests on North Java data in Arc Info.
Currently used methods for representing geographical information are inadequate because they do not tolerate imprecision. This leads to information loss and inaccuracy in analysis. Such expressive inadequacy is largely due to the underlying membership concept of classical set theory. To improve information processing in GIS research and application, an alternative membership concept is required. In this paper, we explore the inadequacy imposed upon geographical information representation by classical set theory and address the problems of information loss. A fuzzy relational data model is defined which is more representative for geographical information. A GIS database for agricultural land resource management is created by using the data model and a new technique for assessing land suitability is developed. The fuzzy representation largely facilitates data analysis in this GIS. The methods are tested with data from North Java, Indonesia using a vector-based GIS software package, Arc Info, and the analysis results are presented.
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L. A. Zadeh · Information and Control · 1965 · 64.9K citations
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E. F. Codd · Communications of the ACM · 1970 · 5.2K citations · Full text
A relational model of data for large shared data banks
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A framework for land evaluation
Rogier van den Brink, Anthony Young · Socio-Environmental Systems Modeling · 1977 · 1.3K citations · Full text